Prof. Dr. Frederick Klauschen
Prof. Dr. Frederick Klauschen
Research Group Lead / Charité
Research Grouplead | BIFOLD
Director | Pathologisches Institut, Ludwig-Maximilian-Universität München
Group Leader
Institute of Pathology
Charité UNIVERSITÄTSMEDIZIN BERLIN
| 2012 | Novartis Pathology-Oncology Award |
| 2011 | Human Frontier Science Program Young Investigator Award |
| 2004 | NIH Postdoctoral Fellowship Award |
Systems biological integration of proteogenomic profiles and histological images through bioinformatics and machine learning with the goal to better understand and predict pathological mechanisms in tumors and finally, to better diagnose and treat cancer.
- German Pathological Society
- International Academy of Pathology
- German Physical Society
Frederick Klauschen, Jonas Dippel, Klaus-Robert Müller
Foundation models in pathology
Philipp Anders, Philipp Erwin Seegerer, Katja Lingelbach, Suhas Pandhe, Sandip Ghosh, Cornelius Böhm, Stephan Tietz, Rosemarie Krupar, Lars Tharun, Marie-Lisa Eich, Julika Ribbat-Idel, Verena Aumiller, Sabine Merkelbach-Bruse, Alexander Quaas, Nikolaj Frost, Georg Schlachtenberger, Matthias Heldwein, Ulrich Keilholz, Khosro Hekmat, Jens-Carsten Rückert, Reinhard Büttner, David Horst, Maximilian Alber, Lukas Ruff, Frederick Klauschen, Gabriel Dernbach, Simon Schallenberg
Abstract 3351: From bench to bedside: generalizable AI model for ADC biomarker evaluation in NSCLC
Albrecht Stenzinger, C. Benedikt Westphalen, Jan Budczies, Daniel Kazdal, Carolin Ploeger, Christian Altbürger, Matthias Evert, Nisar Malek, Peter Schirmacher, Frederick Klauschen
Comprehensive genomic profiling requires a blended ecosystem of learning healthcare and clinical trials
Gabriel Dernbach, Marie-Lisa Eich, Mihnea P. Dragomir, Philipp Anders, Nadia Jurczok, Christian Stief, Philipp Jurmeister, Thorsten Schlomm, Frederick Klauschen, David Horst, Gerald Bastian Schulz, Simon Schallenberg
Spatial expression of HER2, NECTIN4, and TROP-2 in Muscle-Invasive Bladder Cancer and metastases: Implications for pathological and clinical management
Maximilian Alber, Stephan Tietz, Jonas Dippel, Timo Milbich, Timothée Lesort, Panos Korfiatis, Moritz Krügener, Beatriz Perez Cancer, Neelay Shah, Alexander Möllers, Philipp Seegerer, Alexandra Carpen-Amarie, Kai Standvoss, Gabriel Dernbach, Edwin de Jong, Simon Schallenberg, Andreas Kunft, Helmut Hoffer von Ankershoffen, Gavin Schaeferle, Patrick Duffy, Matt Redlon, Philipp Jurmeister, David Horst, Lukas Ruff, Klaus-Robert Müller, Frederick Klauschen, Andrew Norgan
Atlas: A Novel Pathology Foundation Model by Mayo Clinic, Charité, and Aignostics
AI in medicine: new approach for more efficient diagnostics
Researchers from LMU, BIFOLD, and Charité have developed a new AI tool that uses imaging data to also detect less frequent diseases of the gastrointestinal tract. In contrast to conventional models, the new AI only needs training data from common findings to detect deviations.
AI facilitates breakthrough in cancer diagnostics
So-called sinonasal undifferentiated carcinomas (SNUCs) are extremely difficult to diagnose. An interdisciplinary team of researchers has developed an AI tool that reliably distinguishes tumors on the basis of chemical DNA modifications
An overview of the current state of research in BIFOLD
Since the official announcement of the Berlin Institute for the Foundations of Learning and Data in January 2020, BIFOLD researchers achieved a wide array of advancements in the domains of Machine Learning and Big Data Management as well as in a variety of application areas by developing new Systems and creating impactfull publications. The following summary provides an overview of recent research activities and successes.